Revisiting cache block superloading

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Abstract

Technological advances and increasingly complex and dynamic application behavior argue for revisiting mechanisms that adapt logical cache block size to application characteristics. This approach to bridging the processor/memory performance gap has been studied before, but mostly via trace-driven simulation, looking only at L1 caches. Given changes in hardware/software technology, we revisit the general approach: we propose a transparent, phase-adaptive, low-complexity mechanism for L2 superloading and evaluate it on a full-system simulator for 23 SPEC CPU2000 codes. Targeting L2 benefits instruction and data fetches. We investigate cache blocks of 32-512B, confirming that no fixed size performs well for all applications: differences range from 5-49% between best and worst fixed block sizes. Our scheme obtains performance similar to the per application best static block size. In a few cases, we minimally decrease performance compared to the best static size, but best size varies per application, and rarely matches real hardware. We generally improve performance over best static choices by up to 10%. Phase adaptability particularly benefits multiprogrammed workloads with conflicting locality characteristics, yielding performance gains of 5-20%. Our approach also outperforms next-line and delta prefetching. © 2009 Springer Berlin Heidelberg.

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APA

Watkins, M. A., McKee, S. A., & Schaelicke, L. (2009). Revisiting cache block superloading. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5409 LNCS, pp. 339–354). https://doi.org/10.1007/978-3-540-92990-1_25

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